class_docstr: Container mirroring Sklearn anomaly detection API.
docstr: Utility functions used to emulate the behavior of the Sklearn API.
  On anomaly detection (e.g. isolation forest) returns the decision_function score plus offset_
docstr_tok: ["Utility","functions","used","to","emulate","the","behavior","of","the","Sklearn","API",".","On","anomaly","detection","(","e.g",".","isolation","forest",")","returns","the","decision_function","score","plus","offset_"]
code: def score_samples(self, *inputs):
      """
      Utility functions used to emulate the behavior of the Sklearn API.
      On anomaly detection (e.g. isolation forest) returns the decision_function score plus offset_
      """
      return (
          self.decision_function(*inputs)
          + self._extra_config[constants.OFFSET]
      )
  
imports: from abc import ABC, abstractmethod
  from hummingbird.ml._utils import pandas_installed
  from hummingbird.ml.operator_converters import constants
label_desc: Use image node_id 4 for calling the SklearnContainerAnomalyDetection obj's underlying member method code with example usage: obj.score_samples() and returns: unknown